Lake Ice-Water Classification of RADARSAT-2 Images by Integrating IRGS Segmentation with Pixel-Based Random Forest Labeling

Lake Ice-Water Classification of RADARSAT-2 Images by Integrating IRGS Segmentation with Pixel-Based Random Forest Labeling

Changes to ice cover on lakes throughout the northern landscape has been established as an indicator of climate change and variability, expected to have implications for both human and environmental systems. Monitoring lake ice cover is also required to enable more reliable weather forecasting acros...

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Bibliographic Details
Main Authors: Marie Hoekstra, Mingzhe Jiang, David A. Clausi, Claude Duguay
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Remote Sensing
Subjects:
classification
gray-level co-occurrence matrix (GLCM)
iterative region growing using semantics (IRGS)
RADARSAT-2
lake ice
random forest (RF)
Online Access:https://www.mdpi.com/2072-4292/12/9/1425

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https://www.mdpi.com/2072-4292/12/9/1425

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